Fix GPU CuArray ambiguity and type-stable sum for LTS

- Fix CuArray ambiguity: replace (T::Type{<:AnyGPUArray})(VA) = T(Array(VA))
  with T(stack(VA.u)) and add N type parameter to disambiguate against
  CuArray(::AbstractArray{T,N}) from CUDA.jl
- Add type-stable Base.sum(VA::AbstractVectorOfArray) that reduces over
  .u to avoid inference failure on Julia 1.10 with deeply nested type
  parameters (fixes @inferred sum(VA[VA[zeros(4,4)]]) on LTS)

Co-Authored-By: Chris Rackauckas <accounts@chrisrackauckas.com>
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: ChrisRackauckas

src/RecursiveArrayTools.jl

@@ -177,7 +177,8 @@ module RecursiveArrayTools
 
     import GPUArraysCore
     Base.convert(T::Type{<:GPUArraysCore.AnyGPUArray}, VA::AbstractVectorOfArray) = stack(VA.u)
-    (T::Type{<:GPUArraysCore.AnyGPUArray})(VA::AbstractVectorOfArray) = T(Array(VA))
+    # Disambiguate with CuArray(::AbstractArray{T,N}) by providing the typed method
+    (T::Type{<:GPUArraysCore.AnyGPUArray})(VA::AbstractVectorOfArray{<:Any, N}) where {N} = T(stack(VA.u))
 
     export VectorOfArray, VA, DiffEqArray, AbstractVectorOfArray, AbstractDiffEqArray,
         AllObserved, vecarr_to_vectors, tuples

src/vector_of_array.jl

@@ -1118,6 +1118,16 @@ vecarr_to_vectors(VA::AbstractVectorOfArray) = [VA[i, :] for i in eachindex(VA.u
 # linear algebra
 ArrayInterface.issingular(va::AbstractVectorOfArray) = ArrayInterface.issingular(Matrix(va))
 
+# Type-stable sum/mapreduce that avoids inference issues on Julia 1.10
+# with deeply nested VectorOfArray type parameters
+function Base.sum(VA::AbstractVectorOfArray{T}) where {T}
+    return sum(sum, VA.u)::T
+end
+
+function Base.sum(f::F, VA::AbstractVectorOfArray{T}) where {F, T}
+    return sum(u -> sum(f, u), VA.u)
+end
+
 # make it show just like its data
 function Base.show(io::IO, m::MIME"text/plain", x::AbstractVectorOfArray)
     (println(io, summary(x), ':'); show(io, m, x.u))